Wajir South Sub County, Kenya

WAJIR SOUTH SUB COUNTY , KENYA th th 7 to 17 October 2013

Caroline Njeri KIMERE

ACKNOWLEDGEMENTS

Special thanks are expressed to;

• European Commission Humanitarian Office (ECHO) and Department For International Development (DFID) for the continued financial support to Save the Children Nutrition program and for funding this survey.

• Coverage Monitoring Network (CMN) for the support provided through remote technical support by the RECO Inés ZUZA SANTACILIA. This survey would not have been possible without training provided initially and the support received through email during the data collection and analysis.

• The Save the Children International (SCI) team in Wajir South, Wajir East and Nairobi. In particular, the Nutrition Specialist (Irene Soi) for her support in coordinating the SQUEAC survey at the field level. Thanks to the Health and Nutrition Programme Manager (Rahab Kimani) for her collaboration and support. We thank the Nutrition Coordinators (Lynette Dinga and Adan Abdille), Nutrition Officer (Daniel Wanyoike), data clerk (Farah Adan) and the enumerators for their tireless efforts to ensure that the survey was conducted professionally and timely.

• The Ministry of Health (MoH) for their support and commitment especially the County Nutrition Coordinator (Nuria Ibrahim Abdi) and all the health workers who participated in the survey

• The Survey team (enumerators and drivers) for their tireless efforts to ensure that the survey was conducted professionally and on time.

• Community members who willingly participated in the survey and provided the information needed.

• This study would not have been possible without the hard work and commitment of everyone involved.

EXECUTIVE SUMMARY

Wajir South Sub-County is one of the 4 sub-counties in Wajir County in North Eastern Province (NEP) of Kenya. Save the Children has been implementing programmes in Wajir South district since July 2009.. Save the Children has partnered with Ministry of Health (MOH) in Wajir South and Habaswein districts to provide health and nutrition services. Save the Children is supporting 38 locations/settlements (23 outreach sites and 16 health facilities) to integrate management of acute malnutrition (IMAM), provide quality preventive and curative health services, and water sanitation and hygiene (WASH). Currently, 38 Outpatient Therapeutic Programmes (OTP) sites are functioning in both Wajir South and Habaswein district. There is also one stabilization center. Save the Children has supported community-level volunteers who are engaged in screening and mobilizing children under 5 and pregnant and lactating women. They detect cases of some diseases (including malnutrition) and refer them to the outreach sites and health facilities for management. Regarding the nutritional situation, data from SMART survey conducted in May 2013 shows the following: Global Acute Malnutrition and Severe Acute Malnutrition (SAM) rates were 10.5 % (7.9 - 13.5 95% C.I.) and 1.6 % (0.8 -3.1 95% C.I.) respectively. Resume of coverage assessment The coverage assessment was conducted to evaluate access and coverage of the Community based Management of Acute Malnutrition programme for children ages 6 to 59 months with SAM. It conducted between September 6th and 17th October 2013 and it was the fourth Coverage survey to be conducted in Wajir South Sub County. It was conducted at the end of the Haggai dry season. 2013 (October) Year 2010 (April) 2011 (April) 2011 (December)

Assessment SQUEAC SQUEAC SQUEAC SQUEAC

Coverage Point: 61.1% Point: 50.0% Point: 54.0% Point: 42.6% results (95% CI: 43.2-77.1) (95% CI: 29.4-70.7) (95% CI: 39.1-68.8) (95 CI 29.2%-57.0%)

The SQUEAC methodology used consisted of 3 stages, applying the principles of triangulation (by source and method) and sampling to redundancy. The table below presents the main barriers on which the program must act to improve coverage as well as the boosters to the programme coverage.

Barriers Boosters Long Distance to HFs/Outreaches Good inter-linkage between community and (by CHWs follow up) Shortage of Staff at and high Staff turn over Awareness of OTP and MUAC by caretakers and the community RUTF shared, seen as food and sold in the Good mobilization (Acceptance of program) shops Nomadism/Migration Good integration at in services provided (Allows SAM Screening) Lack of ownership of management of Referrals from CHWs malnutrition by MOH Collaboration and referral from TBA

Recommendations

1. Improve on community sensitization 2. Deliberate incorporation of varied sources of referrals (Sheikhs, Traditional healers) 3. Advocacy on Importance of RUTF and on availability of essential drugs 4. Come up with ways to address the chronic staff shortage in the district 5. Improve on the data quality 6. Strengthen joint planning and coordination with MOH and other partners

CONTENTS 1. INTRODUCTION ...... 7 1.1 CONTEXT ...... 7 1.1.1 Overview of the area ...... 7 1.1.2 Nutritional situation...... 8 1.1.3 Health access in Wajir South district...... 9 1.1.4Nutrition services ...... 9 1.2 SAVE THE CHILDREN IN DISTRICT ...... 10 1.3RESULTS OF PREVIOUS SQUEACS IN WAJIR SOUTH ...... 11 2. OBJECTIVES ...... 12 2.1MAIN OBJECTIVE ...... 12 2.2SPECIFIC OBJECTIVES ...... 12 3. METHODOLOGY ...... 13 3.1GENERAL OVERVIEW ...... 13 3.2STAGES...... 14 Stage 1: Identification of potential areas of high and low coverage and access barriers ...... 14 Stage 2: Confirms the location of areas of high and low coverage ...... 15 Stage 3: Wide area survey conducted to estimate overall coverage...... 16 3.3ORGANIZATION OF THE EVALUATION ...... 18

3.3.1 CMN technical support ...... 18 3.3.2 Team training, logistic organization and evaluation development ...... 19 3.4LIMITATIONS ...... 19 4. RESULTS ...... 20 4.1STAGE 1 ...... 20 4.1.1. Recommendations follow up of SQUEAC December 2011 ...... 20 4.1.2. Quantitative data analysis ...... 21 4.1.3. Qualitative data analysis ...... 29 4.2STAGE 2 ...... 30 4.3STAGE 3 ...... 31 1 The prior ...... 31 2 The likelihood ...... 31 3 The posterior ...... 33 5DISCUSSION ...... 34 6.RECOMMENDATIONS ...... 36 Annex 1 : Survey questionnaire for current SAM children NOT in the program ...... 39 Annex 2: Wajir East SQUEAC plan, September – October 2013 ...... 40 Annex 3 : SQUEAC Survey team...... 41 Annex 4 : Terminology in Somali used to describe malnutrition and RUTF. In Wajir South Sub-county, SQUEAC October 2013...... 42 Annex 5: Weighted BBQ, Wajir South SQUEAC, October 2013 ...... 43

ABBREVIATIONS

BBQ Barriers, Boosters and Questions CI Credible Interval CMAM Community Management of Acute malnutrition CMN Coverage Monitoring Network DNOS District Nutrition Officers ECHO European Commission - Humanitarian Aid & Civil Protection FGD Focus Group Discussion GAM Global Acute Malnutrition HC Health Centers HF Health Facility ICCM Integrated Community Case management IMAM Integrated Management of Acute Malnutrition INGO International Non-Governmental Organisation IRK Islamic Relief Kenya LoS Length of Stay MAM Moderate Acute Malnutrition MEAL Monitoring, Evaluation, Accountability and Learning MoH Ministry of Health MUAC Mid-Upper Arm Circumference OCHA Office for the Coordination of Humanitarian Affairs OS Outreach Site OTP Outpatient Therapeutic Programme RUTF Ready to Use Therapeutic Food SAM Severe Acute Malnutrition SC Stabilization Centre SCI Save the Children International SFP Supplementary Feeding Program SQUEAC Semi Quantitative Evaluation of Access and Coverage TBA Traditional Birth Attendants UNDP United Nation Development Programme UNICEF United Nations Children’s Fund WASDA Wajir South Development Association WHO World Health Organisation

1. INTRODUCTION

1.1 CONTEXT

1.1.1 Overview of the area

Wajir South is one of the districts that form Wajir County in North Eastern Province (NEP) and is gazetted as part of the Arid and Semi-Arid Lands of Kenya (ASAL). The district is located in the North West horn of Kenya bordered by Somalia republic to the east, Wajir West district to the West, Lagdera to the south and Wajir East district to the North. The district was in 2010 subdivided into Habaswein and Wajir South districts. The larger Wajir South district administratively consists of 5 divisions including Habaswein, Sabuli, Banane, Kulaaley and Diif. The district population is currently estimated at 137, 9912 persons with a growth rate of 3.7%. Save the Children operates in all the Divisions of Wajir South districts. Within the five divisions there are a total of 16 government health facilities including Habaswein district hospital. Figure 1: Map of counties in Kenya

Rainfall in the district is unpredictable, erratic and inadequate amounting to 250-300 mm annually on average and the district experiences an annual evapo-transpiration of 2500mm apart from the last short rains which was adequate it is also characterized by long dry spells and short rainy seasons which are erratic, unreliable and poorly distributed. Temperatures are normally high ranging between 28-40°C. Soils are mainly sandy and sandy loams. The districts are characterized by chronic food insecurity and high rates of malnutrition. The community is largely pastoralist and pre- dominantly Somali. About 60% -70% of the people depend largely on livestock for their livelihood. The main form of land use is nomadic pastoralism which is seen as the most efficient method of exploiting the range lands hence pastoral activities are practiced all over the district. The District consists largely of a featureless plain. There are three swamps namely Boji, Lagbogol and Lorian all of which are found in Habaswein division. The area receives bi-modal rains with the onset of the long rains in April-May. The months succeeding the long rains, June to September, are very dry but vegetation continues to thrive because the lower temperatures reduce the rate of evaporation. The short rains fall from October to December. The annual precipitation is about 280mm which varies in amount and distribution from year to year. The district’s climatic condition is characterized by recurrent droughts and unreliable rainfall that hinders crop production and growth of pasture for livestock keeping. These cyclic shocks have retarded development in the area since gains of a particular season are wiped out by drought and famine.3

1.1.2 Nutritional situation

Regarding the nutritional situation, Save the Children has been conducting nutritional SMART surveys1 in Wajir South Sub-County since 2009 to date. Figure 2 shows the results of these nutritional surveys. Global acute malnutrition (GAM) rates had surpassed the WHO alert threshold for a state of emergency (>15%) since 2009 to 2012 but in 2013 the levels seems to be dropping. Figure 2: Results of nutrition surveys in Wajir South Sub-County, KENYA. 2009-2013.

1 2006 WHO standards

In the sub county, malnutrition rates had been chronically at emergency levels. These high rates of malnutrition can be attributed to poor health conditions, sub-optimal maternal and child feeding, care practices, and food insecurity. This has been compounded by high rates of poverty and illiteracy, marginalization, recurrent environmental shocks (floods and droughts) and displaced populations adding an additional strain to already weak health systems and communities2.

1.1.3 Health access in Wajir South district

Services are delivered both at outreach sites, which are closer to community level and at primary health care units/dispensaries and at hospital. Since 2009, the Ministry of Health (MoH) had created community units comprising of a team of community-level volunteers (Community Health Workers (CHWs)/ Community Health Volunteers (CHVs)) engaged in screening and mobilizing children under 5 and pregnant and lactating women. . The community has chosen them with the participation of the MoH. The CHVs are trained. They have participated in on-job trainings and classroom trainings about some diseases (especially in children). Most of them have Mid Upper Arm Circumference (MUAC) to conduct screening at the community level. Nurses and Community Health Extensions Workers (CHEWs) are formal salaried workers within the health system. They provide treatment for Severe Acute Malnutrition (SAM) as part of high impact nutrition interventions. In the 2 districts, there are 36 nurses and CHEWs. There are 14 dispensaries, 1 sub-district hospital and 1 district hospital.

1.1.4 Nutrition services

In the 16 Health Facilities (HF) and 23 Outreach Sites (OS), the nutrition services are delivered by the MoH. Currently there are 38 Outpatient Therapeutic Program (OTP) sites functioning in the 2districts (Habaswein and Wajir South). There is one Stabilization Centre (SC) in Habaswein district, Wajir South Sub-county. Since 2009, the MoH started to integrate the in-patient and out-patient management of severe acute malnutrition into hospitals and HF (i.e., at regional and district levels). In 2011, the out-patient management of SAM was further decentralized to the community level. The objective was to ensure access to nutrition services by bringing the service closer to the community. It benefits families by reducing opportunity costs of accessing treatment. It also benefits the health system through capacity building and acts as the catalyst for strengthening nutrition activities within and at the community level, for treatment and prevention of malnutrition. According to the Guidelines for Integrated Management of Acute Malnutrition of 2009, the admission criteria are Weight for Height < 70% (or <-3 Z-score using the WHO-2005 standards),

2 SMART survey report 2013, Kenya Demographic Health Survey 2008

MUAC < 110 mm or presence of bilateral pitting oedema. These assessments are done at the facility level or at the community outreach sites by a nurse or another health worker. Screening at the community level is done by community health workers/volunteers using MUAC and referral for SAM cases are made for cases <125mm to be screened for management either for severe or moderate malnutrition. UNICEF provides the Ready to Use Therapeutic Food (RUTF) and medicines for SAM treatment. Save the Children supports in distribution. For Moderate Acute Malnutrition Management (MAM), Save the Children manages cases of MAM in collaboration with the World Food Programme (WFP) through its implementing partner Wajir South Development Association (WASDA), District Nutrition Officers (DNOs) office, health offices and the community. Supplementary food is provided by WFP.

1.2 SAVE THE CHILDREN IN DISTRICT

Save the Children International (SCI) is partnering with Ministry of Health to provide high impact nutrition intervention Programme whose overall goal is to contribute to a reduction in mortality and morbidity associated with acute malnutrition amongst children under five and women in ASAL of Kenya. The programme is implemented across the two districts in Wajir South sub-county. Save the Children is also working in Wajir East, Mandera Central and Mandera West in the North Eastern Province. The evolution of the programme implementation of Save the Children is shown below.

Figure3: SC implementation strategy for International rescue Committee (IRC), Save the Children (SC) and Islamic Relief Kenya (IRK) 2012-2015.

REDUCTION IN MORTALITY AND MORBIDITY ASSOCIATED WITH ACUTE MALNUTRITION AMONG-5 U CHILDREN AND WOMEN LIVING IN KENYA’S ARID AND SEMI- ARID LANDS

SUSTAINED REDUCTION IN U- 5 PREVALENCE OF ACUTE MALNUTRITION

Strengthen district management and support systems to provide and scale-up quality nutritional services

Change behaviour around maternal, infant, and young child nutrition (MYCN)

Increase number of women and children receiving HINI

Direct Support Mentoring and Follow-up

Role ofIRC, IRK, SC, and WVI Role ofGovernment and Local Partners

Year One Year Two Year Three

The nutrition programme builds on an already established community structure for Integrated Community Case management (ICCM) that refers children under five years with severe acute malnutrition for treatment to community-based OTP sites. The OTP sites are highly decentralized to increase access to prompt and effective treatment. All cases of malnutrition treated are those without complications, while severe cases are referred to the stabilization center in Habaswein district hospital. In 2013 there are 38 OTP sites in 2 districts, 16 of them are HF based in government health structures and 23 are community based.

1.3 RESULTS OF PREVIOUS SQUEACS IN WAJIR SOUTH

In order to assess and improve program performance in terms of access and coverage, three coverage assessments have been carried out. Using the Semi-Quantitative Evaluation of Access and Coverage (SQUEAC) methodology in 2010, March and December 2011 as shown in the table below;

Table 1: Results of coverage assessments, 2010-2012, Wajir South district, North Eastern Province in Kenya.

Year 2010 (March) 2011 (March) 2011 (December) Assessment SQUEAC SQUEAC SQUEAC Zone / OTP Wajir South Sub County Wajir South Sub County Wajir South district sites 23 OS and supporting the MoH in 16 HF MUAC < 115 mm < 115 mm < 115 mm admission Coverage Point: 61.1% Point: 50.0% Point:54.0% results3 (95% CI: 43.2-77.1) (95% CI: 29.4-70.7) (95% CI: 39.1-68.8) Main Bitter Corn Soy blend Current drought situation (lack of 1. Inaccessible roads barriers Inadequate number of water) 2. Migration volunteers and declining Community apathy 3. Insecurity motivation Stigma 4. Timely health seeking Low acceptability of Lack of Program effectiveness 5. Inadequate inclusion of key IMUNUT (Cure trends) sources of referral Limited sources of referrals Lack of adequate screening of new 6.Challenges associated with immigrants and defaulter tracing MoH managing malnutrition Lack of varied sources of referrals within Program waiting time for a 7. Apathy and ignorance in proportion of the community childcare Non-targeted beneficiaries

3 Period coverage: CSAS 2006: 49.1% (95% IC: 33.6- 64.6), SQUEAC 2010 80.6% (95% IC: 70.0- 88.9), March 2011 82.3% (95% IC: 74.1- 88.8), Dec 2012 Cen 55.1- 78.0), other 83.7% (95% IC: 74.0-90.3),

2. OBJECTIVES

2.1 MAIN OBJECTIVE The main objective of this assessment was to evaluate access and coverage of the Integrated Management of Acute Malnutrition (IMAM) for children ages 6 to 59 months with SAM in Wajir South Sub-County, North Eastern region in Kenya, using the Semi-quantitative evaluation of access and coverage (SQUEAC) methodology.

2.2 SPECIFIC OBJECTIVES - To determine baseline coverage for IMAM - To identify boosters and barriers influencing IMAM program access and coverage - To develop feasible recommendations to improve IMAM program access and coverage - To compare and monitor progress since the previous SQUEAC conducted in Wajir South

3. METHODOLOGY4

3.1GENERAL OVERVIEW

The Semi-Quantitative Evaluation of Access and Coverage (SQUEAC) is a coverage assessment method developed by Valid International, FHI 360/FANTA, UNICEF, Concern Worldwide, World Vision International, Action Against Hunger, Tufts University, and Brixton Health. The methodology is “semi-qualitative” in nature, meaning that it draws from a mixture of both quantitative data from routine program monitoring activities as well as qualitative data collected on the field. This mixed methods approach combines data sources to estimate program coverage and to develop practical measures that can improve access and coverage. - Quantitative data came mainly from routine monitoring information that the program already collected including: admissions, defaulting, recovery, middle upper arm circumference (MUAC). Routine program data was coupled with “complementary data” like agriculture, labor, and disease calendars, anthropometric nutritional surveys, and agricultural and food security assessments. - Qualitative data collected came from interviews, focus groups and questionnaires with various key informants. Together, the data were triangulated by source and method to formulate hypotheses about coverage and access. Data triangulation is a powerful technique that helped validate our findings through cross verification. Hypotheses were then tested with small-area surveys and small sample surveys. Then, a wide area survey was conducted in the community to determine the point coverage estimate. Lastly, the results from the quantitative and qualitative analyses and the wide-area likelihood survey were combined and the overall global coverage estimate was calculated using Bayesian statistical techniques. The coverage assessment was fourth coverage study in the area. It was conducted between the 7th to the 17th October 2013. It was carried out at the end of the dry season and when food availability was apparently good. The SQUEAC methodology used consisted of 3 stages, applying the principles of triangulation (by source and method) and sampling to redundancy.

4 2012. SQUEAC and SLEAC Technical Reference. FANTA. Available at http://www.fantaproject.org/sites/default/files/resources/SQUEAC-SLEAC-Technical-Reference-Oct2012_0.pdf

3.2 STAGES

Stage 1: Identification of potential areas of high and low coverage and access barriers

Identification of potential areas of high and low coverage using routine program data; in this stage, triangulation of data is going to be done by various sources and methods as highlighted below. 1. Recommendations follow up of SQUEAC December 2011 Analysis of recommendations from the SQUEAC of December 2011 follows up. The evolution of the factors influencing coverage positively and negatively has been studied. 2. Quantitative data Quantitative, routine program data helped to evaluate the general quality of IMAM services, to identify admission and performance trends and to determine if the program adequately responds to need. It also helped point out problems in screening, admission and reporting. Lastly, routine program data analysis provided the first insights into variation in program performance between OTPs. Route program data analysis (January 2012– June 2013) 39 OTP: 23OS + 16 HF - Global (OTP and SC) trends of admission and defaulters over time and compared to the agricultural calendar, the lean period, child epidemics and diseases, workload, weather patterns and key events - Admission: admission by OTP and SC - OTP and SC program performance indicators over time (recovery, default, death, non- response). - Stock break out data. Complementary data from Health Facility (May – September 2013) for 15 OTP sites ( 6 OS + 9 HF) - MUAC at the time of admission - Discharged o Cured: length of stay (LoS) and MUAC at discharge. o Defaulters: length of stay (LoS) and MUAC at discharge. - OTP admissions by category (MUAC, W/H and Oedema) - The village lists populations belonging to each OTP and distance walking to OTP. Admissions per village Not available - Admissions and defaulters per village - Source of referral to the OTP

3. Qualitative data

Qualitative data was collected to investigate program operations, to unravel the opinions and experiences of actors involved in IMAM and to identify any potential barriers to access. The following methods were used: focus groups, semi-structured interviews, structured interviews, case studies, observation and information from previous coverage assessments. Interviews and focus groups were conducted with key informants either directly or indirectly involved in the IMAM program. These included: women’s and men’s community, SCI program staff, local authorities, OTP/SC nurses, CHW, caregivers of SAM children, Informal caregivers (traditional healers and traditional birth attendants), partners (WFP, WASDA) and mother to mother support group and the sub county HMT. Finally we couldn’t meet county or sub county health authorities. The BBQ framework. Throughout the investigation, the data are going to be organized, analyzed and triangulated using the Barriers, Boosters and Questions (BBQ5) framework. It is a tool that facilitates iterative data collection that is then categorized into one of three categories. The various data organized within the BBQ framework, when combined, will help providing information about where coverage is likely to be satisfactory as well as where it is likely to be unsatisfactory. Additionally, the BBQ provided information about likely barriers to services access that exists within the IMAM program.

Stage 2: Small area surveys Confirms the location of areas of high and low coverage

The goal of stage 2 is to test the hypotheses about coverage and access elaborated in stage 1. These hypotheses usually take the form of identifying areas where the combined data suggest that coverage is likely to be either high or low. The small-area surveys method was used to test the hypotheses for IMAM high and low coverage areas. The active and adaptive case-finding methodology was used to find SAM cases. Data surveys will be analysed using simplified lot quality assurance sampling (LQAS). The LQAS classification technique analyses data using the following formula:

where

5 ‘Barriers’ are negative findings that deter from program coverage and complicate access to service. Conversely, ‘boosters’ contribute to a higher coverage and facilitate access. Lastly, ‘questions,’ are those findings elements to be further investigated, and either become a barrier or booster or remain inconclusive

If the number of covered cases found (that is, those cases in the program) is greater than then then the coverage of the surveyed area is classified as being greater than or equal to the coverage standard .

If the number of covered cases found (that is, those cases in the program) is less than then then the coverage of the surveyed area is classified as being less than or equal to the coverage standard The threshold chosen was 50%. The point coverage SQUEAC results in Wajir South in December 2011 was the guide to establish this threshold. If the number of covered cases found (that is, those cases in the program) is less than then then the coverage of the surveyed area is classified as being less than or equal to the coverage standard .

Stage 3: Building the prior and conducting wide area survey to estimate overall coverage.

The goal of stage three is to calculate the overall coverage estimate. This is done using a Bayesian statistical technique called “beta-binomial conjugate analysis.” Conjugate analysis begins with a beta distributed, probability density called the “prior.” The prior is then combined with a binomial distributed, likelihood function called the “likelihood.” The likelihood was determined through a wide- area coverage survey that was conducted across the entire program catchment area; the mode of the likelihood was, in fact, the point coverage estimate from the survey. Because the prior and the likelihood are mathematically expressed in similar ways (as probability distributions) they can be combined through conjugate analysis, the result of which is the posterior probability density—the “posterior.” The mode of the posterior is the final coverage estimate.

1. The Prior The prior was constructed by combining the results from stages 1 and 2, that is: routine program data, qualitative data and all relevant findings from the small-area and small sample surveys. The prior was the result of combining four modes: 1) The Simple BBQ. The simple BBQ is the first and simplest approach to calculating the prior. A uniform score of 5 points was attributed to each element (either a barrier or booster). The total booster and total barrier scores were summed. The total booster score was then added to the minimum possible coverage (0%) and the total barrier score was subtracted from the maximal possible coverage (100%). The coverage estimate was calculated by taking the mean of these two percentages. 2) The weighted BBQ: a score from 1 to 5 was attributed to each element. The score reflected the relative importance or likely effect that the element had on coverage. The coverage estimate was calculated by the method explained above. 3) The concept map: is a graphical analysis technique that was used to organize the data. The final product, the concept-map, is a diagram that visualizes relationships between findings. It was elaborated within a context frame, which is defined by an explicit focus topic. Links were

drawn between each concept, representing the relationship between them. The various relationships types traced included: results in, leads to, encourages, helps create, allows, etc. Two concept maps were created, for barriers and boosters. For each map, the total number of ‘linkages’ was counted. Like before the booster linkage sum was added to the minimum possible coverage value (0%) while the barrier linkage sum was subtracted from to the maximum possible coverage value (100%). The coverage estimate was calculated by taking the mean of these two percentages. 4) The histogram prior: During a participatory working group, the investigation team designed a histogram representing the prior mode. This was done realistically and democratically by the SQUEAC team. The mode, minimum and maximum coverage values were chosen credibly. Though all the above processes were undertaken in the current survey (the histogram, the concept map, simple BBQ and weighted BBQ) the compilation of the prior was calculated using an excel sheet and when the formula was put into the sheet, it was done wrongly and therefore calculated the prior base on only the simple BBQ and weighted BBQ only hence giving a prior of 40.5% instead of 43.9% that would have been the case if all the parameters had been considered The likelihood A wide-area “likelihood survey” was conducted over the entire program catchment area to calculate the coverage estimate. The active and adaptive case-finding methodology was used to identify the SAM cases. The case definition used for coverage survey was defined as “a child matching the admission criteria of the programme”. The admission criteria of the Kenyan IMAM programme is children aged between 6 and 59 months with at least one of the following criteria: 1) a MUAC of <115 mm and/or 2) W/H < - 3 Z-scores and / or 3) bilateral pitting oedema A simple structured interview questionnaire was used to caregivers of non-covered cases for SAM Annex 1. The sample size required was calculated by using the following equation:

1. Mode: prior value expressed as a proportion. 2. : shape parameters of the prior.

3. αPrecision et β : desired precision. In the present case the precision used was 0.135 (13.5%). 4. SAM prevalence: 0.175% was chosen after stage 2 results. Initially the rates considered were 0.7%, the prevalence in the last SMART survey in May 2013 (for MUAC admission criteria) in Wajir East and South district. But the prevalence was found lower at the second stage and was therefore revised downwards so as to be able to fine the cases.

5. Average village population: 3,830 population in Wajir South (based on district health office data which is projected from the 1999 census since the 2009 data was refuted as inflated) 6. Population between 6 and 59 months : approximately 20.0% And the sample size will was into the minimum number of villages needing to be sampled to achieve the sample size using the following equation:

The number of village required was randomly selected with ENA for SMART software6.

2. Overall Coverage Estimate The point or period coverage estimate was chosen for SAM coverage. By the method of Bayesian beta- binomial conjugate analysis the prior probability density was combined with the coverage estimate from the likelihood survey to calculate the mode of posterior probability density. The Posterior Probability is the estimate of the overall coverage: it represents the synthesis of the prior probability and likelihood generated by the calculator with Bayes credible interval (CI) of 95%. Recommendations and Action Plan: A final important step is the development of an action plan that clearly identifies the actions to be undertaken, indicators, evaluation methods and deadlines. 3.3 ORGANIZATION OF THE EVALUATION

3.3.1 CMN technical support

The team conducting the SQUEAC in Wajir South was made up of participants from SCI, MOH and some enumerators from the community. This was done with remote technical support of the Coverage Monitoring Network (CMN). The CMN Project is a joint initiative by ACF, Save the Children, International Committee, Concern Worldwide, Helen Keller International and Valid International. The programme is funded by ECHO and USAID. This project aims to increase and improve coverage monitoring of the Community Management of Acute malnutrition (CMAM) programme globally and build capacities of national and international nutrition professionals; in particular across the West, Central, East & Southern African countries where the CMAM approach is used to treat acute malnutrition. It also aims to identify, analyze and share lessons learned to improve the IMAM policy and practice across the areas with a high prevalence of acute malnutrition. The remote technical and methodological support was provided by a Regional Coverage Advisor (RECO) Inés ZUZA SANTACILIA through email.

6Available at: http://www.nutrisurvey.de/ena/ena.html

3.3.2 Team training, logistic organization and evaluation development

The investigation team (described in Annex 3) was composed of members of SCI from Wajir, and one person from Nairobi, MoH staff (2 DNOS from Wajir South) and enumerators from the community.

The SQUEAC was conducted in the field by SCI Nutrition Specialist (Irene Soi) with phone support from SCI Nutrition M&E Specialist (Caroline Kimere) and with remote support from CMN RECO (Ines Zuza) through emails.

A two days training in the SQUEAC methodology was made to the enumerators and the DNOs by the Nutrition specialist in Habaswein town followed by the actual survey.

For the three steps the investigation team was divided in five teams, composed of three people each.

3.4 LIMITATIONS The evaluation was limited by the following elements: - Though we had done the concept map and histogram when it came to calculating the prior we used an excel sheet that had a formula that did not include the two hence they were not considered in prior calculation. - Gerille village was not accessible due to the security situation. Some OTP sites were very far off yet the security restrictions do not permit sleep overs in those areas thus forcing the teams to travel vast distances, a case in point being Diff and Dagahley. - It was difficult to establish who referred the children to the OTP sites since this information was not recorded in the admission cards or the registers. - On checking for the OTP admissions by category it was realized in some cases the admission was done by both MUAC and W/H but the information was not correctly captured in the registers. - On the admission information, the village of origin was not always recorded thus difficult to trace the children. - A list of villages in small units was not available. (Some villages are conglomerates of small villages) and some new villages were not included in the official list. SCI manually completed the list of villages. - No updated map of Wajir South/Habaswein was available. - The distances to the OTP sites wasn’t always available - The numbers of cases found at the likelihood stage were less that those anticipated 15 and not 20 as anticipated leading to a wide credible interval and therefore caution is advised at interpretation.

4. RESULTS 4.1 STAGE 1

A. Recommendations follow up of SQUEAC December 2011

Table 2: Resume of the recommendations of the SQUEAC of December 2011 and the follow up, Wajir South, Kenya. October 2013

Recommendations Achieved Not On- Fully Partially Achieve goin d g 1. Community mobilization a. Target all key field sources of referral particularly Sheiks and traditional healers with nutrition education and the need to refer malnourished children to the OTP. √ b. Conduct timely screening of all new immigrants. c. Enhance mobilization activities within the Habaswein district hospital area. √ 2. Community sensitization √ a. Emphasize that after discharge mothers should routinely take children for screening b. Identify homes where caretakers are apathetic and √ conduct individualized health and nutrition education 3. Programming √ a. In collaboration with the administration, map out migratory patterns so that in the event of similar drought, the program can access communities as much as possible. √ b. Establish emergency response strategies for management of malnutrition in areas that may be inaccessible for prolonged periods of time due to e.g. rain or insecurity. √ These may include provision of monthly rations. In addition seek ways to motivate mothers to bring children to the program to reduce on defaulting. 4. Monitoring and evaluation a. The program should seek to record refugees in program as such as much as possible to facilitate in appropriate monitoring of program coverage. √ b. Map out all villages in the site areas and indicate the village of origin on the admission cards to allow for assessment of admissions per village in addition to the √ sites. c. The admission cards should indicate the source of referral to assess the key referral sources in the community. d. Follow-up on program non-respondents. √ 5. Advocacy on aspects affecting management of malnutrition particularly; √

a. The MoH to investigate the reasons for the high turnover of DNOs in the district and address this to facilitate coordination of nutrition activities. √ b. The need for additional resources for the MoH to effectively manage malnutrition c. The need for ownership of management of malnutrition √ by MoH and support to the DNO all the way from the national to district levels. √ d. Retention of health facility nurses in the district e. Feeding programs for the elderly. f. Infrastructure to facilitate in program implementation √ mainly roads. √ 6. Ensure there are adequate buffer stocks to address the √ challenges of pipeline breaks 7. Seek to address on time the factors with potential to be barriers √ to coverage namely: a. Distance to access sites for a proportion of the community b. Consistent provision of drugs by the outreach teams or timely communication to community in case of shortages. √ c. In the event of contaminated consignments, timely and √ adequate re-assurance to the community that the program. √

B. Quantitative data analysis

a. Needs response : admissions and defaulters trends compared to seasonal and key events calendar

Figure 4 below shows the OTP admission over a 20 -month period (January 2012 –August 2013). This graph is aligned with seasonal and Key event calendar developed by the investigation team (weather patterns, seasonal calendar of human diseases associated with SAM in children, food availability, and workload). Together these two figures helped evaluate to what extent the program responds to seasonal needs. There were 65 defaulters along these months’. For the period under review, (Jan 2012 to August 2013), 1808 SAM children were admitted to OTPs and 76 to SC with a mean of 94.2 children admitted per month. 65 defaulters were notified during the period. The SAM admission trends are reflecting few months of the year trends. Defaulting was cumulatively reported at 4%. The hunger gap is from January to Mid-April with a peak March. The admission trends however were low during the hunger gap because the families are sometimes moving with the animals in search of water and pasture. In January 2012 Blanket Supplementary Feeding Programme (BSFP) was on during the said time and the programme seems to have met the community need. Admissions were highest during the rainy which could be attributed to high food cost and the high morbidity rates for diarrhoea and acute respiratory tract infections.

Figure 3: OTP admission and defaulters patterns over time compared with seasonal event calendar, Wajir South Sub- County

2012 2013 Jan Feb Mar Apr May June'1 July Aug Sept Oct Nov Dec Jan'13Feb Mar Apr May June Jul Aug Sept Seasons Rains Diarrhoea ARTI Childhood Morbidity Malaria

Food access Food Prices Herding/watering animals Farming (men) Collecting firewood

Activities Migration (men/Women) (due to drought) Mass screening BSFP Change of implementation Key events Ramadhan

180 160 140 120 100 80 60 Number of cases 40 20 0 Jan Feb March Apr May June July Aug Sept Oct Nov Dec Jan Feb March Apr May June July August months Total (SC + OTP) Total Defaulters

b. OTP vs SC admissions

The percentage of children admitted to the SC could be an indicator of the timeliness of admissions. It is directly related to the percentage of SAM cases that arrive at the OTP with associated medical complications. Children remaining untreated for long periods with declining nutritional status develop medical complications and end up needing SC care. A high percentage of SAM cases with medical complications could often the product of a late presentation and uptake of services. In Wajir South Sub-County the proportion of program admissions requiring inpatient care from January 2012 to August 2013 was 4.0% This percentage is within the 5% recommended for established programs.

Figure 4: OTP admission compared with SC admissions. Wajir South Sub-County, KENYA. January 2012 to August 2013

c. Admissions by OTP

Figure 6 shows the percentage of SAM cases admitted per OTP over a 12-month period (July 2012 – June 2013). Sabuli and Meri OTP’s contributed to most of the cases contributing 15.9% and 14.0% of the cases respectively. The OTP sites with the least admissions were Dilmanyale Kulaaley and Burder. Figure 5: Percentage of SAM admissions per OTP site. Wajir South Sub-County, KENYA. July 2012-June 2013

Figure 7 below shows the percentage of SAM cases admitted per OTP and the percentage of population of the catchment area per OTP over a 15-month period (July 2012 –Sept 2013).

Figure 6: Percentage of SAM admissions per OTP and Percentage of population catchment area. Wajir South Sub County, Kenya. July 2012 -June 2013

Meri, Sabuli, Daghaley, Biyamathow, Diff and Kursin are the ones that received proportionally much more percentage of cases than expected for their catchment area compared to Kulaley, Lehele, Abakore and Habaswein who admitted few compared to their catchment populations. This could be attributed to incorrect catchment population data or inconsistent distribution day’s thus poor attendance by the beneficiaries.

d. Admissions MUAC

Admission MUAC is an indicator for late /early presentation and service uptake at the OTP level. It can be a measure of direct coverage failure because late admissions are those non-covered SAM cases that went untreated for a significant period of time. Late admissions almost always require inpatient care and are associated with prolonged treatment, defaulting and poor treatment outcomes. Figure 6 shows the MUAC distribution for SAM cases admitted by MUAC from January 2012 to September 2013. The admission MUAC criterion is < 110 mm. The MUAC median at admission was 112 mm (in red). That means 50% or the children arrive with a MUAC less than 112 mm with some presenting with a MUAC as low as 90mm. The median MUAC at admission in all OTPs ranged from 105mm and 115mm. The OTP with the least median MUAC at admissions was Argane and Burder (105 mm). And the ones that had the highest median MUAC were; Argane, Hubsoy, Meri, Burder, Dalsan and Salalma all at a median of 115 mm.

Figure 7: MUAC at OTP admission. Wajir South Sub County, KENYA. May-September 2013

e. Admission by type

In the country, admissions for OTP are based on MUAC < 110 mm with (with length > 65 cm), and or WHZ score <-3 and or presence of bilateral pitting edema. In Wajir south admissions were mainly by WHZ score 52.0% (161) followed by MUAC at 46.6% (144) as shown in the figure below. Figure 8: percentage of admissions by the different admission criterion Wajir South May to Sept 2013

f. Performance indicators

The performance indicators for the sub-county were within the acceptable SPHERE standards from July 2012 to July 2013. There were higher defaulting and non-response rates in the month of September 2012 reported 12.0% and 11.0% respectively. This was because of a shift from direct implementation by SCI to supporting the MoH in service provision thus some beneficiaries were not discharged accordingly.

The performance indicators for the SC were at 98.8% cure rates with death rates reported cumulatively at 1.3% from July 2012 to August 2013. Figure 9: Performance Indicators Wajir South January 2012 to June 2013

Looking at the performance indicators per OTP site however some of the OTP sites had 100% cure rates while in some on the sites like Tesorie, lack of essential drugs in the led to non-response for children who had medical complications, thus stayed longer in the programme. In Argane and Kursin, there were high defaulters due to migration of beneficiaries as there was drought. In Habaswein, there were higher cases of either defaulting or non-response since a majority of beneficiaries who had been admitted in Habaswein Hospital had been from the SC and after discharge they never returned to the Hospital to continue with their follow up as most of them came from the neighboring district.

Figure 10: Performance Indicators per OTP site Wajir South Jan 2012 to June 2013

g. Discharged cured

The length of stay before recovery provides helpful insight into the duration of the treatment episode (e.g. the time from admission to discharge). In figure 12 below the OTP median length of stay (LoS) for children cured in the Sub-County was 7 weeks. That means that 50% of those cured stayed beyond 7 weeks with some staying up to 15 weeks. This could be partly attributed to data quality in that there was no tracking of absenteeism with some of the children who could have been discharged as defaulters not being discharged. The international standards define typical LoS should be between 30-40 days (4 to 6 weeks) to a maximum of 8 weeks. In this case the maximum length of stay was >15 weeks Figure 11: Length of stay for discharge cured. Wajir East Sub-County, KENYA. May-August 2013

h. Defaulters

Figure 13 shows the median length of stay before defaulting in Wajir South (March to Aug 2013). A Short length of stay before default can suggest a poor reception or communication between beneficiary and health staff. On the other hand defaulters after several weeks of treatment could be related to long length stays (caretaker assuming the children is cured or tired of keeping on the treatment). In total there were 29 defaulters recorded over a duration of four months preceding the survey. It was however noted that there were issues with data (some children who could have been discharged as defaulters were not discharged since follow up dates were not observed and they therefore ended up in some case being discharged as cured instead). For this reason, the analysis of the defaulters must be interpreted with caution and further information is needed to draw conclusion.

Of the 29 defaulters, the median week at defaulting was 4 weeks. There were defaulters both at the beginning of the treatment and after several weeks of treatment (9). Most of the defaulters defaulting at the first week came from Daghaley health facility which could be attributed to beneficiaries preferring the refugee camps as there is distribution of non-food items such as plastic sheeting and soap to the beneficiaries. The long length of stay could also have been a contributing factor to defaulting at week nine with some mothers losing interest after being in the program for a while. The median MUAC at the last visit for defaulters is 111 mm. This means that 50% of the children defaulted from the program before being recovered. Figure 12: OTP Length of stay before defaulting, Wajir South Sub-County, KENYA. May to August 2013.

C. Qualitative data analysis

The qualitative methods used included focus groups, semi-structured and structured interviews, cases studies and observations. Doing so revealed boosters and barriers. Interviews and focus groups were conducted in villages across the sub county. Questionnaire guides were adapted and oriented to facilitate the collection of data pertinent to program coverage and access. The investigation team also elaborated a list of terminology in the local languages (Annex 4) related to malnutrition and the RUTF. Qualitative data was triangulated by both method and source. All findings were indexed daily into the three-pane BBQ framework (complete BBQ can be found in Annex 5). Table 1 lists the sources and methods used during qualitative data collection. Questions ("Q") that appeared along stage one were analyzed and resolved within days. Table 3: SQUEAC BBQ framework legend, Wajir South Sub-County, KENYA, October 2013

Code Source Code Method Code Zone 1. SAM caretakers A. Group Discussion C Central 2. SCI Staff B. Semi Structured R Rest 3. Traditional Healers/Traditional Birth Interview Attendants (TBAs) C. Case Study 4. CHWs D. Observation 5. Health workers E. Data Analysis 6. Local authorities (religious, chief F. Last SQUEAC Dec 2011- villages/elders/CHCs/) jan 2012 7. Mother to mother support group 8. Community men 9. Community women 10. MoH/Sub-county health Authorities 11. Partners (WASDA/ALDEF/WVI) Table 4 details the principal factors that either negatively or positively influenced program coverage and access during the qualitative data analysis in Wajir East; these are the main barriers and boosters. Table 4: Main program barriers and boosters after qualitative data analysis, Wajir South Sub-county, Kenya, October 2013

Barriers Boosters Long Distance to HFs/Outreaches Awareness of malnutrition Shortage of Staff at and high Staff turn over Awareness of OTP programme/health education RUTF shared, seen as food and sold in the shops RUTF seen as medicine by community members and caretakers Nomadism/Migration Good collaboration with Chiefs/CHW, Nurse/CHW, Community/CHW. Planned Active Case Finding with CHWs

Lack of ownership of management of malnutrition Referral of cases by CHW/TBAs/Leaders by MOH

4.2 STAGE 2 This stage confirms the location of areas of high and low coverage and the reasons for coverage failure identified in Stage 1 using small studies, small surveys or small-area surveys. The routine program, quantitative and qualitative data collected in stage one, when combined, helped identify areas within the intervention zone where coverage was likely to be either satisfactory or unsatisfactory. This information was used to formulate hypotheses about coverage that were tested. Small-area surveys methodology were used to test this hypotheses. Areas with high coverage were agreed to be areas with an active CHW and with a health worker (nurse or clinical officer) while the ones without would have low coverage. Table 5: Small-area survey selected villages for, Wajir South Sub-County, KENYA. October 2013

Low Coverage SAM areas Outreach Zone CHW HW Insecurity site / HF

Argane Outreach Rest Yes No Habaswein HF Central Yes (NA) Yes (NA) No Dilmanyale HF Rest Yes No Diff No Central No Yes Boji Outreach Rest Yes No Mathaliba HF 7 km Central Yes No High coverage SAM areas Outreach Zone CHW HW Insecurity site / HF Meri HF R Active Yes No Sabuli HF R Active Yes Yes Fedwein & Damajale Outreach R Active Yes No Lagbogol Outreach R Active Yes No Biyamathow Outreach R Active Yes No

The LQAS classification technique was used to analyze the data. The threshold value « p » used was 50%, and the results have been the following. - Low coverage: n=2 (two SAM cases were found); none of these cases was covered in OTP. d = (2 x (50/100) =1. Since 0 < 1 » there was confirmation of hypothesis of low coverage area.

- High coverage: n=8 (eight SAM cases were found); 5 of these cases were in OTP while three cases were not covered. d = (8 x (50/100) =4. Since 5 is >4» the hypothesis of high coverage area was confirmed.

4.3 STAGE 3

1 The prior

As explained in the methods, the prior mode for the SAM program is normally calculated using the mean of the four coverage estimates: 1. The simple BBQ (weighed by 5); 2. The weighted BBQ; 3. The concept map 4. The histogram prior. However in the current survey though the four parameters had been calculated, the calculation for the prior was done in an excel sheet and the formula was not put incorrectly and therefore instead of an average of the four parameters being considered only two were (simple BBQ and Weighted BBQ) as shown in Table 6 below; Table 6: SAM program prior probability mode calculation, Wajir South, KENYA, October 2013

Boosters Barriers Results (in %)

Simple BBQ*5 18 23 ((18*5))+ (100-(23*5)))/2 37.5 Weight BBQ 50 63 (50+ (100-63))/2 43.5

Averaged prior 40.5

Next, using the equations presented in methodology 3, the shape parameters and were calculated with a prior mode of 40.5% about which the range of uncertainty was 15.5% and 65.5%. was 13.6 and was 20.1. The distribution of the prior probability density has a mode at 40.5% and a 95% “credible interval” (i.e. the Bayesian equivalent of the 95% confidence interval) as shown in figure 14 below. Figure 13: SAM prior coverage (binomial probability density), Wajir South, KENYA October 2013

2 The likelihood Sample size

The sample size was calculated using the equation described in methodology (for the “n likelihood”). In the present SAM program SQUEAC the sample size for the likelihood survey used a precision of 0.135 (13.5%). And the minimum number of children to be sampled was 19.1 rounded off to 20. The sample size was then translated into the minimum number of villages needing to be sampled to achieve the sample size using the equation of “n villages” described in the methodology part. With a revised estimated SAM prevalence of 0.175% in Wajir South and a median village population of 3,830 inhabitants (20% of which approximately are between 6 and 59 months) the minimum number of villages to be sampled was 14.2 rounded off to 15. They were randomly selected (described in methodology). Active case-finding

The 15 selected villages were divided up among the investigation team. Stage 3 lasted for 3 days. All the 15 selected villages were accessed. In total, 12 SAM cases were identified. Six of these children were covered and in OTP while six were not. Additionally recovering cases were found. To determine if there were cases both card and RUTF were used. The final precision for the survey in Wajir South was 14.6 compared to the initial 13.5 precision used during the planning session. The lowered precision was due to fewer numbers of cases found in the wide area survey. Table 7: Results of the SAM active case-finding Wajir East Sub-county KENYA, October 2013

SAM covered SAM not Recovering SAM cases cases covered cases cases 12 6 6 14 A questionnaire was administered to caregivers of the 6 non-covered cases to find out why their children were not in the program (Annex 2). Of the 6 caregivers questioned, all 100% realized their children were malnourished five of these (83.0%) knew of a program to treat it. The reasons why they did not take their children are detailed in figure 15. Figure 14: Barriers to SAM service uptake found by the likelihood survey, Wajir South Sub County, KENYA. October 2013.

3 The posterior The point coverage estimate was selected as the most appropriate indicator for this investigation. One of the main reasons for this selection was 1) the large length of stay for SAM children in the OTP service, 2) the poor quality of data suspected in the . By method of Bayesian beta-binomial conjugate analysis the prior probability density was combined with the likelihood function to calculate the posterior—the final coverage estimate: 42.6% (29.2%-57.0% 95 CI) Figure 16 is a graph of the three probability densities. It shows that both the prior (blue curve) and posterior (red curve) probability densities, and the likelihood survey (green curve). The prior and the likelihood do not conflict, but there is a wide distribution for the likelihood. This is due to the low number of cases found during stage 3 (less than 20 SAM cases - the minimum sample size calculated) that makes the likelihood smaller than the prior (see figure 16), results must be then taken with precaution. This also explains the big CI (from 29.2% to 57.0%). For following SQUEACs, the minimum sample size for the likelihood needs to be found. If the prevalence of SAM is very low in the moment of the SQUEAC it will be necessary to study wheteher to continue with stage 3 until a minimum number of cases is ensure. Figure 15: SAM program posterior coverage, Wajir South, Kenya. October 2013.

5. DISCUSSION

This SQUEAC investigation in Wajir South showed a point coverage estimate of 42.6% (29.2%-57.0% 95 CI) The coverage was below the SPHERE standards for a rural population (>50%). A number of barriers identified during the SQUEAC that could have influenced the coverage and access in the district: - The chronic shortage of qualified staff at is still a problem to contend with. Out of the 16 and 23 outreach sites in Wajir South/Habaswein, only 13 have qualified nurses running actively and offering the much sought after services. With all these facilities except the District hospital having only one staff at a time, it means that when the staff is away or unwell, then the facility is closed down and the outreaches are affected as well. This therefore leads to staff overworking and with time leads to high staff turnover. - Lack of awareness on the admission a criterion by some caretakers means that there is perceived rejection of their children thus leading to a negative perception of the programme in this manner. This could be attributed to poor or lack of health education to the caretakers on malnutrition, and admission criteria. Because of this, most mothers expressed their wish to have their children in the programme and if not then they relayed a negative message to other mothers thus discouraging them from taking their children for screening. - In Wajir South/Habaswein, shortage of essential drugs in some of the health facilities was a negative factor in attracting mothers to present their children at the Outpatient Therapeutic Program (OTP). This means that children with other underlying medical conditions would not be treated appropriately and mothers would then prefer to seek other alternative treatment for their children. - A major issue of concern is the poor quality of data witnessed at the various Outpatient Therapeutic Programs (OTPs) that were visited. Registers were not filled in correctly and mostly could not give an accurate picture of how the programme was performing. Details such as admission criteria, dates of discharge and the anthropometry on discharge were either missing or not correctly indicated. Dates on which the beneficiaries were absent were skipped and therefore difficult to determine the length of stay for some cases. Some beneficiaries that had been defaulters earlier had not been exited from the programme appropriately. - RUTF is shared amongst children within the household as it is seen as food. Most caretakers and community members said that since RUTF makes children put on weight and become healthy, then they would like to have all their children eat the product. In addition to this, RUTF is readily available for purchase in the market going for as low as KSh 20 hence people in the community were able to purchase and consume. Upon further enquiry, it was found that most of the stocks were either sourced from the Daadab refugee camps or from Somalia due to the proximity of the border points. Thus, mothers do not have to enroll their children for OTP in order to access the RUTF.

Promoters of coverage - Awareness of malnutrition and how it presents in children was a plus for programme coverage. Due to the continuous presence of programmes that educate the masses on health and nutrition issues, the community members could identify malnutrition and even have local terms to explain the condition. Thus, there is room for improvement. - Community awareness of OTP programme was also as a result of availability of these treatment programmes for severe acute malnutrition. Continuous mobilization and screening at the community level has had a positive impact within the community in terms of awareness of the services that the MoH in collaboration with SCI offers to the community. - Referral of cases by community health workers, TBA and community leaders of cases screened or suspected to be malnourished was a huge contribution to the coverage of the programme. Since the CHWs are few and have large distances to cover, considering that they are volunteers, means that they are not able to do active case finding as effectively as they should and in addition to this do mobilization and participate actively during distribution days. Therefore, TBAs and community leaders are a welcome contribution to educating the masses on seeking for timely treatment for the malnourished children. - Regular feedback by the MoH and SCI team to the implementing teams was a marked plus and this was reiterated by the community health workers and nurses and nutritionists. This meant that feedback to the teams on the ground led to improvements on issues that were discussed during supportive supervision and On the Job Training (OJT) sessions. Constant communication and discussions amongst the teams leading to better outputs. - Due to the chronic staff shortage and very high turnover, a situation that is the norm in the north eastern region in Kenya, CHWs who have been working for many years and have acquired basic medical skills have found themselves stepping in for the health workers when required. This has ensured that services continue in the absence of trained staff, albeit the compromised quality of service. This though was identified as a booster to the programme.

6. RECOMMENDATIONS

Based on the results above there are some factors that could contribute negatively to program coverage in Wajir South sub district. The following recommendations and action plan were developed to address them. No RECOMMENDATIONS RATIONALE/EVIDENCE 1 Improve on community • Belief on discrimination of admission to OTP sensitization • Beneficiaries from nomadic groups defaulting • Long distance to health facilities and outreach sites sited as a barrier 2 Deliberate incorporation of • Lack of adequate involvement of key leaders in varied sources of referrals referral of cases (Sheikhs, Traditional healers) 3 Advocacy on Importance of RUTF • RUTF shared, seen as a food and should in shop. and on availability of essential • Availability of plumpy nut in shops drugs • Lack of essential drugs at 4 Come up with ways to address • High workload to CHWs the Chronic staff shortage in the • Inadequate active case finding and follow up at district community level by CHWs • Inadequate staff • Shortage of Staff 5 Improve on the data quality • Registers not well filled in the health facilities • High length of stay attributed to data quality 6 Strengthen Joint planning and • Competition priorities leading to interference with coordination with MOH and other OTP program partners • Lack of ownership of management of malnutrition by MoH It is important to share the results of the investigation SQUEAC with the MoH and partners involved in IMAM. IF possible a presentation of the results should be presented to the IC staff, MoH and partners. And giving a feedback to the HAD could help to improve their work. The action plan defined for implementing the recommendations (with indicators) will help to improve the coverage after this assessment. The proposed recommendations were worked on with in conjunction with the MoH in the field

Action Plan for the survey recommendations

Source Of Recommendations Activities Timelines Indicators Who Verification 1. Improve on - Educate Dec-Feb - 1 quarterly Sensitization DNO, DPHO community community on 2014 meeting with reports sensitization criteria of community admission to OTP members and program to avoid the nomadic belief of populations DNO/DPHN discrimination - sensitize nomadic Dec-Jan caregivers that 2014 they can access nutrition services at sites close to where they are moving too and encourage to move near places they can access services 2. Deliberate - Have special Quarterly - 1 sensitization Sensitization DNO/DMO incorporation of forums with key session in all the report H/CNC varied sources of leaders to sensitize division per Training referrals them on nutrition quarter report. (Sheikhs, and the programs - One Training Referral sheets - Give the sheikhs session on basic from Sheikhs Traditional basic nutrition Jan- June malnutrition for healers) training on MUAC 2014 Sheikhs and and have them Traditional refer children with healers malnutrition who come to them 3. Advocacy on - Creation of By- Jan 2014 - Meetings for Final copy of DNO/CNC/ Importance of laws at County coming up with the bi laws partners RUTF and on level to avoid sale bi laws held availability of of RUTF March 2014 - No of advocacy No of advocacy Division of essential drugs - Advocacy at sessions held at sessions nutrition National level to national and prohibit sale of Jan 2014 KEMSA levels DPHN/CPH RUTF N - Advocacy at County level on KEMSA supply distribution 4. Come up with - Do an assessment Jan 2014 - No of Assessment DNO/DPHN ways to address of available staff assessment report /DMOH the Chronic staff and their cadre and done. shortage in the what gap there is March 2014 - No of advocacy Advocacy CNC/CPHN/ district to fill in staffing sessions had on report PS - Advocating for recruitment of recruitment of staff additional staff at County level 5. Improve on the - Strengthen data Monthly - I data Meeting DNO/DPHN

data quality quality through: management minutes /DHRIO - Having in-charges meeting with meetings to share Jan 2014 facility DMOH/DPH data and incharges N corrections 6. Strengthen Joint - Strengthen Monthly - 1 meeting per Meeting MoH/partn planning and planning and month minutes ers coordination coordination between partners with MOH and other partners

Annex 1 : Survey questionnaire for current SAM children NOT in the program 1. DO YOU THINK YOU CHILD IS SICK? ____ if yes: WHICH DISEASE?______2. DO YOU THINK YOUR CHILD IS MALNOURISHED (local word to describe it)?  YES  NO (STOP) 3. DO YOU KNOW OF A PROGRAM THAT CAN HELP MALNOURISHED CHILDREN?  YES  NO (STOP) If yes, what is the name of the program? ______

4. WHY YOUR CHILD IS CURRENTLY NOT ENROLLED IN THE PROGRAM? Do NOT prompt Ask “Anything else?” Several answers are possible

Answers Tick Notes

1. No time/ Too busy (what is the caretaker’s occupation? ______)

2. OTP site too far away (how long does it take to walk? ______)

3. There is no one else who can take care of the other siblings

4. No money for the treatment

5. The child has been previously rejected (When? ______approximately) 6. Has been to the clinic but the child was not referred (When? ______approximately)

7. I do not think the program can help the child (prefer traditional healer, etc.)

8. Waiting time too long

9. Mother feels ashamed or shy about coming

10. Mother sick

11. Spouse does not allow

12. Other reasons (specify) :

5. WAS YOUR CHILD PREVIOUSLY ADMITTED TO THE OTP PROGRAM?  YES  NO (→ stop !) If yes, why is he/ she not enrolled anymore ?  Defaulted : When ? ______Why ?______ Condition improved and discharged by the program : When ? ______ Discharged while he has not recovered : When ? ______ Other : ______

Thank the caretaker and give a referral slip. Inform the caretaker of the OTP and date to attend

Annex 2: Wajir South SQUEAC plan, October 2013 Stages Activities S M T W T F S S M T W T 6 7 8 9 10 11 12 13 14 15 16 17

Travel of SCI Team to Habaswein X

Training on coverage/SQUEAC methodology. Workshop of data analysis X (1 days) 1 "on the job-training" : quantitative data collection in and interviews ( and X X X community) Work on the BBQ (3 days)

Active and Adaptative Research Training (3 hours) X Teams depart for field 2 Small area surveys Finalising BBQ (+/- weigth BBQ) X X (2 days)

Data Synthesis. Weight BBQ + / - Histogramme + / - Concept map. X 3 Build a prior probability. Sampling / Preparation of big area surveys. (1 day)

Big area survey (3 days) X X X

Report and Develop recommendations and report. (1 X recomme Day) ndations

SCI Team travel back to Wajir base

Annex 3: SQUEAC Survey team

List of Team members for SQUEAC Survey Wajir South 6 (35.3%) women and 11 (64.7%) men.

Team NAME Sex Team PHONE NUMBER Number (Women/Men) 1 Irene Soi W Coordinating-SCI 0722 487 556 W Team Leader – 2 Khadija Mohamed 0714 340 892 DNO

3 Saladha Mohamed W Team Leader-DNO 0722 487 446 4 Adan Abdille M Team Leader SCI 0723 812 131 5 Daniel Wanyoike M Team Leader SCI 0727 957 385 6 Lynette Dinga W Team Leader SCI 0725 681 922 7 Farah Adan M Meal SCI 0720 339 957 8 Abdirahaman M. Malele M Enumerator 0721 540 110 9 Abdi Mohamed Ibrahim M Enumerator 0721 841 626 10 Adey Abdi Adan M Enumerator 0718 002 828 11 Abdirahman Hirsi M Enumerator 0720 323 487 12 Abdullahi Mohamed Ismail M Enumerator 0723 201 027 13 Farhiya Rashid W Enumerator 0725 612 121 14 Abdi mohamed Adan-Banin M Enumerator 0720 306 842 15 Siyat Abdullahi M Enumerator 0726 886 075 16 Halima K6 womenassim W Enumerator 0721 624 698 17 Mohamed Mahamud Ali M Enumerator 0723 864 790

Annex 4: Terminology in Somali used to describe malnutrition and RUTF. In Wajir South Sub-county, SQUEAC October 2013

The table has been updated from terminology obtained in previous SQUEACs in the district

Malnutrition and Related Terms Local Names Language Fresh skin rubbing Makhardub Somali Lack of breastfeeding Nasmoga Somali Herbal root Tiira Somali Wasted Kalasibit Somali Plumpynuts Biscuit bajikho Somali Pneumonia Warenta Somali Malnutrition Nafakha daaro Somali Oedima Baarar Somali Old man face Waaji dukheed Somali False teeth Elkow Somali Diarrhea Shuban Somali Malnourished Garaaw Somali Malnutrition Nafaqadari Somali CHW Deryela Somali Herbal medicine Malmal Somali A believe Tawsi Somali Wild fruits used for treatment Gosay Somali

Fear of curse Dajis Somali Used for the treatment of stomach Gurufin Somali upset and persistent vomiting

Used for the treatment of sick Lobadin Somali children(local herbal)

Ghee Siheen Somali Kwashiorkor Anow Somali

Annex 5: Weighted BBQ, Wajir South SQUEAC, October 2013

* Barriers and boosters underlined are those that had a match in the other side. They were chosen to stay in one side because they were strength there. This elimination was taken in account when assigning the points.

**Colours indicate the number of times the information has appeared from the same source or method: once-black, twice-green, thrice- blue and ≥ four times- red

Pts. Boosters Source* Method* Zone Pts. Barrier Source* Method Zone 1 4 Awareness of malnutrition 1, 3,4,6,7,8,9 A,B, C C, R 2 Poor follow up in community/ACF 1,5,9,6 C,B,A RC

2 4 Awareness of OTP 1, 3, 4, A,B,C R,C 2 Poor coordination (SCI& OTP TEAM)Late 5 B C programme/health education 5,6,7,8,9 start at OTP (vehicles arrive late/TRANSPORT) 3 2 Good follow up (home visit)with 1,4,5,7 A,B,C C,R 4 Long distance to OTP/HF 1, 6,7,3,5,4,9 A, B, C R, C caregivers BY CHWS 4 2 RUTF as medicine 1,3,4,5,6,7,8 A,B,C C,R 4 Myths associated with RUTF 3,5,6,8,9 A,B C,R Anthropometry (causes diarrhoea), Negative perception of RUTF 5 1 No rejection in programme 2,4,10 B,D C 5 RUTF as food 1,6,3,5,8,9,4 B, C R, C Anthropometry taken correctly

6 3 Good collaboration with 1,3,4,5,6,7,8 A,B,C C,R 3 Poor health seeking behaviour 1, 3, 4,5, 6, 7, B, A R, C Chiefs/CHW, Nurse/CHW, 8 Community/CHW Planned ACF with CHWs 7 4 Regular feedback from MoH/SCI 4,5 B C,R 5 Nomadism 1, 3,4, 5, 6, 7, A,B, C, R, C 8,9 8 2 Accessibility to OTPs 1,6,7 A,B,C C,R 3 Mother/caretaker busy 1, 4, 5, 6,7 A, B, C R,C

9 3 No stock outs of RUTF 1,5 C,B C,R 2 Not able to identify malnutrition 1,9 B,C R

10 4 No defaulters 1,3,4,5,6,7,8 A,B,C R 2 Not aware of MUAC/OTP 1,3, 6 B,C R,C

11 5 Referral of cases by 1,3,4,5,6,7,8,9 A,B,C R 1 Long stay in programme 1 C R CHW/TBAs/Leaders 12 3 Appreciation of OTP program 3,4,,6,8,9 A,B 5 High workload/Shortage of staff 4, 5,6,7,9 A, B R

13 1 Collaboration with Traditional 3,4 A,B R 4 Shortage of essential drugs 3,4,5, 9 A, B R Healers/TBA

14 4 CHWs stepping in for HW to 6,9 A,B R 1 No NFIs given at OTP 6,9 B R,C ensure continuity of services 15 2 Good health seeking behaviour 1,4,7 A,B,C R 2 Poor collaboration between 6, 7 A,B R leaders/MtMSG & CHW 16 1 Key messages given to OTP 4,1 B,C R 4 Not aware of admission criteria (believe 1,4,6,7 A,B.C R caregivers there’s discrimination) 17 3 Good mobilization by CHWs 1,5,6,7 A,B,C R 3 Competing priorities 4,8 A,B R

18 2 Good record keeping 2,10 D R 2 No health education at distribution site 1 A,D R

19 1 Lack of community mobilisation 2,10 D R

20 1 No feedback to CHW 4 B R

21 1 Insecurity 4 B R

22 5 Data quality issues 2,10 D R

23 1 Lack of appreciation of OTP programme 5 B R